{ "_id": "6ac4a976f511ae58c099f9fa", "Package": "rlibkriging", "Type": "Package", "Title": "Kriging Models using the 'libKriging' Library", "Version": "1.0-0", "Date": "2026-10-04", "Authors@R": "c(person(given = \"Yann\",\nfamily = \"Richet\",\nrole = c(\"aut\",\"cre\"),\nemail = \"yann.richet@asnr.fr\",\ncomment = c(ORCID = \"0000-0002-5677-8458\")),\nperson(given = \"Pascal\",\nfamily = \"Havé\",\nrole = c(\"aut\"),\nemail = \"hpwxf@haveneer.com\"),\nperson(given = \"Yves\",\nfamily = \"Deville\",\nrole = c(\"aut\"),\nemail = \"deville.yves@alpestat.com\"),\nperson(given = \"Conrad\",\nfamily = \"Sanderson\",\nrole = c(\"ctb\"),\nemail = \"conradsand.uq@gmail.com\"),\nperson(given = \"Ciyou\",\nfamily = \"Zhu\",\nrole = c(\"ctb\")),\nperson(given = \"Richard\",\nfamily = \"Byrd\",\nrole = c(\"ctb\")),\nperson(given = \"Jorge\",\nfamily = \"Nocedal\",\nrole = c(\"ctb\")),\nperson(given = \"Jose Luis\",\nfamily = \"Morales\",\nrole = c(\"ctb\")),\nperson(given = \"Mike\",\nfamily = \"Smith\",\nrole = c(\"ctb\"),\nemail = \"grimbough@gmail.com\")\n)", "Maintainer": "Yann Richet ", "Description": "Interface to 'libKriging' 'C++' library\n that should provide most\nstandard Kriging / Gaussian process regression features (like\nin 'DiceKriging', 'kergp' or 'RobustGaSP' packages).\n'libKriging' relies on Armadillo linear algebra library (Apache\n2 license) by Conrad Sanderson, 'lbfgsb_cpp' is a 'C++' port\naround by Pascal Have of 'lbfgsb' library (BSD-3 license) by\nCiyou Zhu, Richard Byrd, Jorge Nocedal and Jose Luis Morales\nused for hyperparameters optimization.", "License": "Apache License (>= 2)", "Encoding": "UTF-8", "SystemRequirements": "GNU make, cmake (>= 3.2.0), gcc", "URL": "https://github.com/libKriging", "Config/pak/sysreqs": "cmake make", "Repository": "https://yannrichet-asnr.r-universe.dev", "Date/Publication": "2026-07-06 19:52:46 UTC", "RemoteUrl": "https://github.com/yannrichet-asnr/rlibkriging", "RemoteRef": "HEAD", "RemoteSha": "36e1392ad0fa465cf753843f576e5d61d96a4591", "Config/roxygen2/version": "8.1.0", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-10-04 12:40:44 UTC", "User": "root" }, "Author": "Yann Richet [aut, cre] (ORCID: ),\nPascal Havé [aut],\nYves Deville [aut],\nConrad Sanderson [ctb],\nCiyou Zhu [ctb],\nRichard Byrd [ctb],\nJorge Nocedal [ctb],\nJose Luis Morales [ctb],\nMike Smith [ctb]", "_user": "yannrichet-asnr", "_type": "src", "_file": "rlibkriging_1.0-0.tar.gz", "_fileid": "https://r2.ropensci.org/74c05043d6d449b9c42c21ac772b2606194ec3d2a34fd53b011780d8d6d26131", "_filesize": 3020393, "_sha256": "74c05043d6d449b9c42c21ac772b2606194ec3d2a34fd53b011780d8d6d26131", "_expires": "2027-01-12T12:48:54.000Z", "_created": "2026-10-04T12:40:44.000Z", "_published": "2026-10-06T07:55:34.385Z", "_jobs": [ { "job": 112165151138, "time": 89, "config": "linux-devel-arm64", "r": "4.7.0", "check": "FAIL", "artifact": "" }, { "job": 112165151170, "time": 111, "config": "linux-devel-x86_64", "r": 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"_maintainer": { "name": "Yann Richet", "email": "yann.richet@asnr.fr", "login": "yannrichet-asnr", "description": "", "uuid": 148193180, "orcid": "0000-0002-5677-8458" }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.2", "role": "Depends" }, { "package": "Rcpp", "role": "LinkingTo" }, { "package": "RcppArmadillo", "role": "LinkingTo" }, { "package": "Rcpp", "version": ">= 1.0.12", "role": "Imports" }, { "package": "methods", "role": "Imports" }, { "package": "DiceKriging", "role": "Imports" }, { "package": "testthat", "role": "Suggests" }, { "package": "utils", "role": "Suggests" }, { "package": "foreach", "role": "Suggests" }, { "package": "roxygen2", "role": "Suggests" }, { "package": "RobustGaSP", "role": "Suggests" } ], "_owner": "yannrichet-asnr", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2025-47", "n": 1 }, { "week": "2025-50", "n": 2 }, { "week": "2025-51", "n": 12 }, { "week": "2025-52", "n": 14 }, { "week": 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"extra/contents.json", "extra/manual.pdf", "extra/readme.html", "extra/readme.md", "extra/rlibkriging.html" ], "_homeurl": "https://github.com/yannrichet-asnr/rlibkriging", "_realowner": "yannrichet-asnr", "_cranurl": true, "_releases": [ { "version": "0.7-0", "date": "2022-09-22" }, { "version": "0.7-2", "date": "2023-01-06" }, { "version": "0.7-3", "date": "2023-01-14" }, { "version": "0.7-3.1", "date": "2023-01-14" }, { "version": "0.7-4", "date": "2023-01-14" }, { "version": "0.7-4.1", "date": "2023-01-18" }, { "version": "0.7-4.2", "date": "2023-02-02" }, { "version": "0.7-4.3", "date": "2023-02-13" }, { "version": "0.8-0", "date": "2023-06-23" }, { "version": "0.8-0.1", "date": "2023-11-28" }, { "version": "0.9-0", "date": "2024-08-26" }, { "version": "0.9-0.1", "date": "2024-08-27" }, { "version": "0.9-0.4", "date": "2024-10-02" }, { "version": "0.9-1", "date": "2025-01-17" }, { "version": "0.9-2", "date": "2025-07-22" }, { "version": "0.9-2.1", "date": "2025-07-23" }, { "version": "0.9-2.2", "date": "2025-08-27" }, { "version": "0.9-2.3", "date": "2025-10-17" }, { "version": "0.9-3", "date": "2026-01-27" }, { "version": "1.0-0", "date": "2026-05-13" }, { "version": "1.1-0", "date": "2026-07-11" }, { "version": "1.1-1", "date": "2026-07-12" }, { "version": "1.2-2", "date": "2026-09-23" }, { "version": "1.2-3", "date": "2026-09-25" } ], "_exports": [ "activation", "as.km", "beta", "centerX", "centerY", "copy", "covMat", "F_", "feature_dim", "fit", "hidden_dims", "is_fitted", "kernel", "KM", "Kriging", "leaveOneOut", "leaveOneOutFun", "leaveOneOutVec", "load", "load.Kriging", "logLikelihood", "logLikelihoodFun", "logMargPost", "logMargPostFun", "M", "MLPKriging", "NestedKriging", "normalize", "predict", "regmodel", "save", "scaleX", "scaleY", "sigma2", "simulate", "T_", "theta", "update", "update_simulate", "warp_affine", "warp_boxcox", "warp_categorical", "warp_knots", "warp_kumaraswamy", "warp_mlp", "warp_neural_mono", "warp_none", "warp_ordinal", "warping", "WarpKriging", "X", "y", "z" ], "_help": [ { "page": "activation", "title": "Get activation function name", "topics": [ "activation" ] }, { "page": "activation.MLPKriging", "title": "Get activation function for an MLPKriging model", "topics": [ "activation.MLPKriging" ] }, { "page": "as.km", "title": "Coerce an Object into a 'km' Object", "topics": [ "as.km" ] }, { "page": "as.km.Kriging", "title": "Coerce a 'Kriging' object into the '\"km\"' class of the 'DiceKriging' package.", "topics": [ "as.km,Kriging,Kriging-method", "as.km.Kriging" ] }, { "page": "as.list.Kriging", "title": "Coerce a 'Kriging' Object into a List", "topics": [ "as.list,Kriging,Kriging-method", "as.list.Kriging" ] }, { "page": "beta", "title": "Get trend coefficients beta", "topics": [ "beta" ] }, { "page": "beta.MLPKriging", "title": "Get trend coefficients beta for an MLPKriging model", "topics": [ "beta.MLPKriging" ] }, { "page": "beta.WarpKriging", "title": "Get trend coefficients beta for a WarpKriging model", "topics": [ "beta.WarpKriging" ] }, { "page": "centerX", "title": "Get input centering vector", "topics": [ "centerX" ] }, { "page": "centerX.MLPKriging", "title": "Get input centering vector for an MLPKriging model", "topics": [ "centerX.MLPKriging" ] }, { "page": "centerX.WarpKriging", "title": "Get input centering vector for a WarpKriging model", "topics": [ "centerX.WarpKriging" ] }, { "page": "centerY", "title": "Get output centering value", "topics": [ "centerY" ] }, { "page": "centerY.MLPKriging", "title": "Get output centering value for an MLPKriging model", "topics": [ "centerY.MLPKriging" ] }, { "page": "centerY.WarpKriging", "title": "Get output centering value for a WarpKriging model", "topics": [ "centerY.WarpKriging" ] }, { "page": "classKriging", "title": "Shortcut to provide functions to the S3 class \"Kriging\"", "topics": [ "classKriging" ] }, { "page": "classMLPKriging", "title": "Shortcut to provide functions to the S3 class \"MLPKriging\"", "topics": [ "classMLPKriging" ] }, { "page": "classNestedKriging", "title": "Shortcut to provide functions to the S3 class \"NestedKriging\"", "topics": [ "classNestedKriging" ] }, { "page": "classWarpKriging", "title": "Shortcut to provide functions to the S3 class \"WarpKriging\"", "topics": [ "classWarpKriging" ] }, { "page": "copy", "title": "Duplicate object.", "topics": [ "copy" ] }, { "page": "copy.Kriging", "title": "Duplicate a Kriging Model", "topics": [ "copy,Kriging,Kriging-method", "copy.Kriging" ] }, { "page": "copy.MLPKriging", "title": "Deep copy of MLPKriging model", "topics": [ "copy.MLPKriging" ] }, { "page": "copy.WarpKriging", "title": "Deep copy of WarpKriging model", "topics": [ "copy.WarpKriging" ] }, { "page": "covMat", "title": "covariance function", "topics": [ "covMat" ] }, { "page": "covMat.Kriging", "title": "Compute Covariance Matrix of Kriging Model", "topics": [ "covMat,Kriging,Kriging-method", "covMat.Kriging" ] }, { "page": "F_", "title": "Get trend matrix F", "topics": [ "F_" ] }, { "page": "F_.MLPKriging", "title": "Get trend matrix F for an MLPKriging model", "topics": [ "F_.MLPKriging" ] }, { "page": "F_.WarpKriging", "title": "Get trend matrix F for a WarpKriging model", "topics": [ "F_.WarpKriging" ] }, { "page": "feature_dim", "title": "Get feature dimensionality (d_out)", "topics": [ "feature_dim" ] }, { "page": "feature_dim.MLPKriging", "title": "Get feature dimensionality for an MLPKriging model", "topics": [ "feature_dim.MLPKriging" ] }, { "page": "feature_dim.WarpKriging", "title": "Get feature dimensionality of warped space", "topics": [ "feature_dim.WarpKriging" ] }, { "page": "fit", "title": "Fit model on data.", "topics": [ "fit" ] }, { "page": "fit.Kriging", "title": "Fit 'Kriging' object on given data.", "topics": [ "fit.Kriging" ] }, { "page": "fit.MLPKriging", "title": "Fit an MLPKriging model to data", "topics": [ "fit.MLPKriging" ] }, { "page": "fit.WarpKriging", "title": "Fit a WarpKriging model to data", "topics": [ "fit.WarpKriging" ] }, { "page": "hidden_dims", "title": "Get hidden layer sizes", "topics": [ "hidden_dims" ] }, { "page": "hidden_dims.MLPKriging", "title": "Get hidden layer sizes for an MLPKriging model", "topics": [ "hidden_dims.MLPKriging" ] }, { "page": "is_fitted", "title": "Check if the model has been fitted", "topics": [ "is_fitted" ] }, { "page": "is_fitted.MLPKriging", "title": "Check whether an MLPKriging model is fitted", "topics": [ "is_fitted.MLPKriging" ] }, { "page": "is_fitted.WarpKriging", "title": "Check whether a WarpKriging model is fitted", "topics": [ "is_fitted.WarpKriging" ] }, { "page": "kernel", "title": "Get kernel name", "topics": [ "kernel" ] }, { "page": "kernel.WarpKriging", "title": "Get kernel name", "topics": [ "kernel.WarpKriging" ] }, { "page": "KM", "title": "Create an 'KM' Object", "topics": [ "KM" ] }, { "page": "KM-class", "title": "S4 class for Kriging Models Extending the '\"km\"' Class", "topics": [ "KM-class" ] }, { "page": "Kriging", "title": "Create an object with S3 class '\"Kriging\"' using the 'libKriging' library.", "topics": [ "Kriging" ] }, { "page": "leaveOneOut", "title": "Compute Leave-One-Out", "topics": [ "leaveOneOut" ] }, { "page": "leaveOneOut.Kriging", "title": "Get leaveOneOut of Kriging Model", "topics": [ "leaveOneOut,Kriging,Kriging-method", "leaveOneOut.Kriging" ] }, { "page": "leaveOneOutFun", "title": "Leave-One-Out function", "topics": [ "leaveOneOutFun" ] }, { "page": "leaveOneOutFun.Kriging", "title": "Compute Leave-One-Out (LOO) error for an object with S3 class '\"Kriging\"' representing a kriging model.", "topics": [ "leaveOneOutFun,Kriging,Kriging-method", "leaveOneOutFun.Kriging" ] }, { "page": "leaveOneOutVec", "title": "Leave-One-Out vector", "topics": [ "leaveOneOutVec" ] }, { "page": "leaveOneOutVec.Kriging", "title": "Compute Leave-One-Out (LOO) vector error for an object with S3 class '\"Kriging\"' representing a kriging model.", "topics": [ "leaveOneOutVec,Kriging,Kriging-method", "leaveOneOutVec.Kriging" ] }, { "page": "load", "title": "Load any Kriging Model from a file storage. Back to base::load if not a Kriging object.", "topics": [ "load" ] }, { "page": "load.Kriging", "title": "Load a Kriging Model from a file storage", "topics": [ "load.Kriging" ] }, { "page": "load.MLPKriging", "title": "Load an MLPKriging model from file", "topics": [ "load.MLPKriging" ] }, { "page": "load.WarpKriging", "title": "Load a WarpKriging model from file", "topics": [ "load.WarpKriging" ] }, { "page": "logLikelihood", "title": "Compute Log-Likelihood", "topics": [ "logLikelihood" ] }, { "page": "logLikelihood.Kriging", "title": "Get Log-Likelihood of Kriging Model", "topics": [ "logLikelihood,Kriging,Kriging-method", "logLikelihood.Kriging" ] }, { "page": "logLikelihood.WarpKriging", "title": "Log-likelihood of the fitted model", "topics": [ "logLikelihood.WarpKriging" ] }, { "page": "logLikelihoodFun", "title": "Log-Likelihood function", "topics": [ "logLikelihoodFun" ] }, { "page": "logLikelihoodFun.Kriging", "title": "Compute Log-Likelihood of Kriging Model", "topics": [ "logLikelihoodFun,Kriging,Kriging-method", "logLikelihoodFun.Kriging" ] }, { "page": "logLikelihoodFun.MLPKriging", "title": "Evaluate log-likelihood at given GP theta", "topics": [ "logLikelihoodFun.MLPKriging" ] }, { "page": "logLikelihoodFun.WarpKriging", "title": "Evaluate log-likelihood at given theta", "topics": [ "logLikelihoodFun.WarpKriging" ] }, { "page": "logMargPost", "title": "Compute log-Marginal Posterior", "topics": [ "logMargPost" ] }, { "page": "logMargPost.Kriging", "title": "Get logMargPost of Kriging Model", "topics": [ "logMargPost,Kriging,Kriging-method", "logMargPost.Kriging" ] }, { "page": "logMargPostFun", "title": "log-Marginal Posterior function", "topics": [ "logMargPostFun" ] }, { "page": "logMargPostFun.Kriging", "title": "Compute the log-marginal posterior of a kriging model, using the prior XXXY.", "topics": [ "logMargPostFun,Kriging,Kriging-method", "logMargPostFun.Kriging" ] }, { "page": "M", "title": "Get whitened trend matrix M", "topics": [ "M" ] }, { "page": "M.MLPKriging", "title": "Get whitened trend matrix M for an MLPKriging model", "topics": [ "M.MLPKriging" ] }, { "page": "M.WarpKriging", "title": "Get whitened trend matrix M for a WarpKriging model", "topics": [ "M.WarpKriging" ] }, { "page": "MLPKriging", "title": "Create an MLPKriging model (Deep Kernel Learning)", "topics": [ "MLPKriging" ] }, { "page": "NestedKriging", "title": "Create an object with S3 class '\"NestedKriging\"' using the 'libKriging' library.", "topics": [ "NestedKriging" ] }, { "page": "NoiseKM", "title": "Create a KM object with heteroscedastic noise (deprecated)", "topics": [ "NoiseKM" ] }, { "page": "normalize", "title": "Get normalize flag", "topics": [ "normalize" ] }, { "page": "normalize.MLPKriging", "title": "Get normalize flag for an MLPKriging model", "topics": [ "normalize.MLPKriging" ] }, { "page": "normalize.WarpKriging", "title": "Get normalize flag for a WarpKriging model", "topics": [ "normalize.WarpKriging" ] }, { "page": "NuggetKM", "title": "Create a KM object with nugget effect (deprecated)", "topics": [ "NuggetKM" ] }, { "page": "predict-KM-method", "title": "Prediction Method for a 'KM' Object", "topics": [ "predict,KM-method" ] }, { "page": "predict.Kriging", "title": "Predict from a 'Kriging' object.", "topics": [ "predict.Kriging" ] }, { "page": "predict.MLPKriging", "title": "Predict with an MLPKriging model", "topics": [ "predict.MLPKriging" ] }, { "page": "predict.NestedKriging", "title": "Predict from a 'NestedKriging' object.", "topics": [ "predict.NestedKriging" ] }, { "page": "predict.WarpKriging", "title": "Predict with a WarpKriging model", "topics": [ "predict.WarpKriging" ] }, { "page": "print.Kriging", "title": "Print the content of a 'Kriging' object.", "topics": [ "print.Kriging" ] }, { "page": "print.NestedKriging", "title": "Print a 'NestedKriging' object.", "topics": [ "print.NestedKriging" ] }, { "page": "regmodel", "title": "Get regression model type", "topics": [ "regmodel" ] }, { "page": "regmodel.MLPKriging", "title": "Get regression model type for an MLPKriging model", "topics": [ "regmodel.MLPKriging" ] }, { "page": "regmodel.WarpKriging", "title": "Get regression model type for a WarpKriging model", "topics": [ "regmodel.WarpKriging" ] }, { "page": "save", "title": "Save a Kriging Model inside a file. Back to base::save if argument is not a Kriging object.", "topics": [ "save" ] }, { "page": "save.Kriging", "title": "Save a Kriging Model to a file storage", "topics": [ "save,Kriging,Kriging-method", "save.Kriging" ] }, { "page": "save.MLPKriging", "title": "Save an MLPKriging model to file", "topics": [ "save.MLPKriging" ] }, { "page": "save.WarpKriging", "title": "Save a WarpKriging model to file", "topics": [ "save.WarpKriging" ] }, { "page": "scaleX", "title": "Get input scaling vector", "topics": [ "scaleX" ] }, { "page": "scaleX.MLPKriging", "title": "Get input scaling vector for an MLPKriging model", "topics": [ "scaleX.MLPKriging" ] }, { "page": "scaleX.WarpKriging", "title": "Get input scaling vector for a WarpKriging model", "topics": [ "scaleX.WarpKriging" ] }, { "page": "scaleY", "title": "Get output scaling value", "topics": [ "scaleY" ] }, { "page": "scaleY.MLPKriging", "title": "Get output scaling value for an MLPKriging model", "topics": [ "scaleY.MLPKriging" ] }, { "page": "scaleY.WarpKriging", "title": "Get output scaling value for a WarpKriging model", "topics": [ "scaleY.WarpKriging" ] }, { "page": "sigma2", "title": "Get process variance", "topics": [ "sigma2" ] }, { "page": "sigma2.WarpKriging", "title": "Get process variance (concentrated MLE)", "topics": [ "sigma2.WarpKriging" ] }, { "page": "simulate-KM-method", "title": "Simulation from a 'KM' Object", "topics": [ "simulate,KM-method" ] }, { "page": "simulate.Kriging", "title": "Simulation from a 'Kriging' model object.", "topics": [ "simulate.Kriging" ] }, { "page": "simulate.MLPKriging", "title": "Simulate from an MLPKriging model", "topics": [ "simulate.MLPKriging" ] }, { "page": "simulate.WarpKriging", "title": "Simulate from a WarpKriging model", "topics": [ "simulate.WarpKriging" ] }, { "page": "T_", "title": "Get Cholesky factor T", "topics": [ "T_" ] }, { "page": "T_.MLPKriging", "title": "Get Cholesky factor T for an MLPKriging model", "topics": [ "T_.MLPKriging" ] }, { "page": "T_.WarpKriging", "title": "Get Cholesky factor T for a WarpKriging model", "topics": [ "T_.WarpKriging" ] }, { "page": "theta", "title": "Get GP range parameters", "topics": [ "theta" ] }, { "page": "theta.WarpKriging", "title": "Get GP range parameters", "topics": [ "theta.WarpKriging" ] }, { "page": "update_simulate", "title": "Update simulation of model on data.", "topics": [ "update_simulate" ] }, { "page": "update_simulate.Kriging", "title": "Update previous simulation of a 'Kriging' model object.", "topics": [ "update_simulate.Kriging" ] }, { "page": "update_simulate.MLPKriging", "title": "Update simulated paths with new observations (FOXY algorithm)", "topics": [ "update_simulate.MLPKriging" ] }, { "page": "update_simulate.WarpKriging", "title": "Update simulated paths with new observations (FOXY algorithm)", "topics": [ "update_simulate.WarpKriging" ] }, { "page": "update-KM-method", "title": "Update a 'KM' Object with New Points", "topics": [ "update,KM-method" ] }, { "page": "update.Kriging", "title": "Update a 'Kriging' model object with new points", "topics": [ "update.Kriging" ] }, { "page": "update.MLPKriging", "title": "Update an MLPKriging model with new observations", "topics": [ "update.MLPKriging" ] }, { "page": "update.WarpKriging", "title": "Update a WarpKriging model with new observations", "topics": [ "update.WarpKriging" ] }, { "page": "warp_affine", "title": "Affine warping: w(x) = a*x + b", "topics": [ "warp_affine" ] }, { "page": "warp_boxcox", "title": "Box-Cox warping", "topics": [ "warp_boxcox" ] }, { "page": "warp_categorical", "title": "Categorical embedding", "topics": [ "warp_categorical" ] }, { "page": "warp_knots", "title": "Piecewise-linear monotone warping with knots (Xiong et al. 2007)", "topics": [ "warp_knots" ] }, { "page": "warp_kumaraswamy", "title": "Kumaraswamy CDF warping on [0,1]", "topics": [ "warp_kumaraswamy" ] }, { "page": "warp_mlp", "title": "Per-variable MLP warping (unconstrained, multi-dim output)", "topics": [ "warp_mlp" ] }, { "page": "warp_neural_mono", "title": "Monotone neural network warping", "topics": [ "warp_neural_mono" ] }, { "page": "warp_none", "title": "No warping (identity)", "topics": [ "warp_none" ] }, { "page": "warp_ordinal", "title": "Ordinal warping (learned ordered positions)", "topics": [ "warp_ordinal" ] }, { "page": "warping", "title": "Get warping specifications as strings", "topics": [ "warping" ] }, { "page": "warping.WarpKriging", "title": "Get warping specification for a WarpKriging model", "topics": [ "warping.WarpKriging" ] }, { "page": "WarpKriging", "title": "Create a WarpKriging model", "topics": [ "WarpKriging" ] }, { "page": "X", "title": "Get training input matrix", "topics": [ "X" ] }, { "page": "X.MLPKriging", "title": "Get training input matrix", "topics": [ "X.MLPKriging" ] }, { "page": "y", "title": "Get training output vector", "topics": [ "y" ] }, { "page": "y.MLPKriging", "title": "Get training output vector", "topics": [ "y.MLPKriging" ] }, { "page": "z", "title": "Get whitened residuals z", "topics": [ "z" ] }, { "page": "z.MLPKriging", "title": "Get whitened residuals z for an MLPKriging model", "topics": [ "z.MLPKriging" ] }, { "page": "z.WarpKriging", "title": "Get whitened residuals z for a WarpKriging model", "topics": [ "z.WarpKriging" ] } ], "_readme": "https://github.com/yannrichet-asnr/rlibkriging/raw/HEAD/README.md", "_rundeps": [ "DiceKriging", "Rcpp", "RcppArmadillo" ], "_sysdeps": [ { "shlib": "libopenblasp-r0", "package": "libopenblas0-pthread", "headers": "libopenblas0-pthread", "source": "openblas", "version": "0.3.32+ds-5", "name": "openblas", "homepage": "https://www.openblas.net/", "description": "Optimized BLAS (linear algebra) library (shared lib, pthread)" }, { "shlib": "libarpack", "package": "libarpack2t64", "headers": "libarpack2-dev", "source": "arpack", "version": "3.9.1-6build1", "name": "arpack", "homepage": "https://github.com/opencollab/arpack-ng", "description": "Fortran77 subroutines to solve large scale eigenvalue problems" }, { "shlib": "libgomp", "package": "libgomp1", "source": "gcc", "version": "16-20260322-1ubuntu1", "name": "openmp", "homepage": "http://gcc.gnu.org/", "description": "GCC OpenMP (GOMP) support library" }, { "shlib": "libstdc++", "package": "libstdc++6", "source": "gcc", "version": "16-20260322-1ubuntu1", "name": "c++", "homepage": "http://gcc.gnu.org/", "description": "GNU Standard C++ Library v3" } ], "_score": 5.4284587735155805, "_indexed": true, "_nocasepkg": "rlibkriging", "_universes": [ "yannrichet-asnr" ], "_binaries": [ { "r": "4.6.1", "os": "linux", "version": "1.0-0", "date": "2026-10-04T12:42:20.000Z", "distro": "resolute", "arch": "x86_64", "commit": "36e1392ad0fa465cf753843f576e5d61d96a4591", "fileid": "https://r2.ropensci.org/6b5aa364e76df63b2c83d18c51eed277ccef76ae39856a5ffdd806a65f2e59b5", "status": "success", "buildurl": "https://github.com/r-universe/yannrichet-asnr/actions/runs/37202648971" } ] }